Update pages/3_Life Cycle Of ML Project.py

pages/3_Life Cycle Of ML Project.py

@@ -2,7 +2,9 @@ import streamlit as st
 
 # Function to display content based on button click
 def display_content(stage):
-    if stage == "Problem Definition":
+    if stage == "Overview":
+        st.markdown("### Overview\nThis application guides you through the lifecycle of a machine learning project.")
+    elif stage == "Problem Definition":
         st.markdown("### Problem Definition\nIdentify the problem you want to solve and set clear objectives and success criteria.")
     elif stage == "Data Collection":
         st.markdown("### Data Collection\nGather relevant data from various sources and store it in a structured format.")
@@ -24,32 +26,22 @@ def display_content(stage):
         st.markdown("### Documentation and Reporting\nDocument the entire project and share the results and insights with stakeholders.")
 
 # Title and Introduction
-st.title("LifeCycle of Machine Learning Project")
+st.title("Lifecycle of a Machine Learning Project")
 st.markdown("Click on a stage to learn more about it.")
 
-# Buttons for each stage
-st.button("Problem Definition", on_click=display_content, args=("Problem Definition",))
-st.button("Data Collection", on_click=display_content, args=("Data Collection",))
-st.button("Data Preparation", on_click=display_content, args=("Data Preparation",))
-st.button("Exploratory Data Analysis (EDA)", on_click=display_content, args=("Exploratory Data Analysis (EDA)",  ))
-st.button("Model Selection", on_click=display_content, args=("Model Selection", ))
-st.button("Model Training", on_click=display_content, args=("Model Training",))
-st.button("Model Evaluation", on_click=display_content, args=("Model Evaluation", ))
-st.button("Model Deployment", on_click=display_content, args=("Model Deployment",))
-st.button("Model Maintenance", on_click=display_content, args=("Model Maintenance", ))
-st.button("Documentation and Reporting", on_click=display_content, args=("Documentation and Reporting", ))
+# Overview button
+if st.button("Overview"):
+    display_content("Overview")
 
-# Author Details
-author_name = "Your Name"
-author_email = "your.email@example.com"
-author_website = "https://yourwebsite.com"
+# Buttons for each stage with colors and emojis
+st.button("🌟 Problem Definition", on_click=display_content, args=("Problem Definition",), key="problem_definition", help="Identify the problem you want to solve and set clear objectives and success criteria.", style="background-color: #FF6347; color: white;")
+st.button("📊 Data Collection", on_click=display_content, args=("Data Collection",), key="data_collection", help="Gather relevant data from various sources and store it in a structured format.", style="background-color: #4682B4; color: white;")
+st.button("🛠️ Data Preparation", on_click=display_content, args=("Data Preparation",), key="data_preparation", help="Clean, transform, and engineer features from the data to prepare it for modeling.", style="background-color: #32CD32; color: white;")
+st.button("🔍 Exploratory Data Analysis (EDA)", on_click=display_content, args=("Exploratory Data Analysis (EDA)",), key="eda", help="Visualize and analyze the data to understand its distributions and relationships.", style="background-color: #FFD700; color: black;")
+st.button("🤖 Model Selection", on_click=display_content, args=("Model Selection",), key="model_selection", help="Choose appropriate machine learning algorithms and develop a baseline model.", style="background-color: #FF4500; color: white;")
+st.button("🏋️ Model Training", on_click=display_content, args=("Model Training",), key="model_training", help="Train the model using the training data and optimize its parameters.", style="background-color: #1E90FF; color: white;")
+st.button("📈 Model Evaluation", on_click=display_content, args=("Model Evaluation",), key="model_evaluation", help="Assess the model's performance using various metrics and cross-validation techniques.", style="background-color: #8A2BE2; color: white;")
+st.button("🚀 Model Deployment", on_click=display_content, args=("Model Deployment",), key="model_deployment", help="Integrate the trained model into a production environment and monitor its performance.", style="background-color: #FF1493; color: white;")
+st.button("🔧 Model Maintenance", on_click=display_content, args=("Model Maintenance",), key="model_maintenance", help="Periodically retrain the model with new data and update features as needed.", style="background-color: #00CED1; color: white;")
+st.button("📝 Documentation and Reporting", on_click=display_content, args=("Documentation and Reporting",), key="documentation_reporting", help="Document the entire project and share the results and insights with stakeholders.", style="background-color: #FF69B4; color: white;")
 
-st.markdown(
-    f"""
-    <h3 style='text-align: left; color: green;'>Author Details</h3>
-    <p><strong>Author:</strong> {author_name}</p>
-    <p><strong>Email:</strong> {author_email}</p>
-    <p><strong>Website:</strong> <a href='{author_website}' target='_blank'>Visit Here</a></p>
-    """,
-    unsafe_allow_html=True
-)